Software Alternatives, Accelerators & Startups

stickK VS Scikit-learn

Compare stickK VS Scikit-learn and see what are their differences

stickK logo stickK

stickK enables users to form commitment contracts to help them achieve their personal goals.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • stickK Landing page
    Landing page //
    2022-10-14
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

stickK videos

Stickk For Accountability (Eric Worre Feature)

More videos:

  • Tutorial - How To Stick To Your Goals (Stickk com Review)

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to stickK and Scikit-learn)
Productivity
100 100%
0% 0
Data Science And Machine Learning
Habit Building
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

Share your experience with using stickK and Scikit-learn. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare stickK and Scikit-learn

stickK Reviews

We have no reviews of stickK yet.
Be the first one to post

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than stickK. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

stickK mentions (6)

  • 90 Day Challenge
    I started a blog kadonis.blogspot.org where I posted about my 90 Day Challenge to improve my lifestyle. I'll be posting with various weekly updates so stay tuned! Feel free to also support me on stickk.com with my commitments! Source: 12 months ago
  • Bryan Johnson - Live Event
    Doctor Hershfield shared stickk.com as a tool. I can also recommend the Forfeit and Squad Apps for accountability and habit formation as well as r/Accountabilibuddies. Source: about 1 year ago
  • Looking for an accountability partner with Stickk - I pay if I miss my goal
    I would like to find someone who could help me accountable with the website stickk.com. Source: about 1 year ago
  • Join Me in a Commitment Contract to Reduce Screen Time
    I am just like many of you, a verified screentime junkie to the point where I get headaches and digital dementia. I've tried so many damn things to reduce my screen time: greyscale the screen, lock away my phone in a safe, use the app/web blockers.. And while these can help, from my experience they just aren't good enough. The one thing I found to legitimately reduce my screen is to have a commitment contract with... Source: about 1 year ago
  • Study/Life
    Would you be willing to use the website stickk.com? Source: almost 2 years ago
View more

Scikit-learn mentions (28)

  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 12 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: over 1 year ago
View more

What are some alternatives?

When comparing stickK and Scikit-learn, you can also consider the following products

Coach.me - Coach.me is a coach that goes everywhere with you, helping you achieve any goal, change any habit, or build any expertise.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Beeminder - Beeminder

OpenCV - OpenCV is the world's biggest computer vision library

GoalsWon - Human accountability coaching for busy people

NumPy - NumPy is the fundamental package for scientific computing with Python